This repository is an official PyTorch implementation of the VSpSR from NTIRE21, Learning SR Space.
We provide scripts for reproducing all the results. You can train your model from scratch, or use a pre-trained model to get different sr images.
VSpSR is built in Python 3.6 using PyTorch 1.7.1. Use the following command to install the requirements:
pip install -r requirements.txt
You can test our super-resolution algorithm with your images. Place your images in any folder you like. (like test).
Run the script in src folder. Before you run the demo, please uncomment the appropriate line in demo.sh that you want to execute.
cd VSpSR # You are now in */VSpSR
sh demo.shYou can find the result images from output folder.
We used DIV2K from NTIRE21 dataset to train our model. Please download it from tr_1X, tr_4X, tr_8X, va_1X, va_4X, va_8X.
Download all the files to any place you want(like NTIRE2021). Then, change the dataset_root argument in demo.sh to the place where DIV2K images are located.
You can train VSpSR by yourself. All scripts are provided in the demo.sh.
One 12-GB Titan X GPU is used for training VSpSR. Training takes about 13 hours.
cd VSpSR # You are now in */VSpSR
sh demo.sh